TY - GEN
T1 - Optimal airline ticket purchasing using automated user-guided feature selection
AU - Groves, William
AU - Gini, Maria L
PY - 2013
Y1 - 2013
N2 - Airline ticket purchase timing is a strategic problem that requires both historical data and domain knowledge to solve consistently. Even with some historical information (often a feature of modern travel reservation web sites), it is difficult for consumers to make true cost-minimizing decisions. To address this problem, we introduce an automated agent which is able to optimize purchase timing on behalf of customers and provide performance estimates of its computed action policy based on past performance. We apply machine learning to recent ticket price quotes from many competing airlines for the target flight route. Our novelty lies in extending this using a systematic feature extraction technique incorporating elementary user-provided domain knowledge that greatly enhances the performance of machine learning algorithms. Using this technique, our agent achieves much closer to the optimal purchase policy than other proposed decision theoretic approaches for this domain.
AB - Airline ticket purchase timing is a strategic problem that requires both historical data and domain knowledge to solve consistently. Even with some historical information (often a feature of modern travel reservation web sites), it is difficult for consumers to make true cost-minimizing decisions. To address this problem, we introduce an automated agent which is able to optimize purchase timing on behalf of customers and provide performance estimates of its computed action policy based on past performance. We apply machine learning to recent ticket price quotes from many competing airlines for the target flight route. Our novelty lies in extending this using a systematic feature extraction technique incorporating elementary user-provided domain knowledge that greatly enhances the performance of machine learning algorithms. Using this technique, our agent achieves much closer to the optimal purchase policy than other proposed decision theoretic approaches for this domain.
UR - http://www.scopus.com/inward/record.url?scp=84896063123&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84896063123&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84896063123
SN - 9781577356332
T3 - IJCAI International Joint Conference on Artificial Intelligence
SP - 150
EP - 156
BT - IJCAI 2013 - Proceedings of the 23rd International Joint Conference on Artificial Intelligence
T2 - 23rd International Joint Conference on Artificial Intelligence, IJCAI 2013
Y2 - 3 August 2013 through 9 August 2013
ER -